readme updated

priyam314 · Mar 21, 2023 · d7178eb · d7178eb
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@@ -172,13 +172,37 @@ From above experiments we can infer that in `content_layer: 4` canvas has lost s
 
 In `content_layer: 0` we can see that style is well composed over canvas while also preserving the content representation, same can be said for `content_layer: 1` but with less prominence. So for further experiment lets' use `content_layer: 0` and `Adam` for fast computation. Currently we have seen all the canvases generated by `conv` layers, lets experiment with `relu` now.
 
+| Content_Layers |                              0                               |                              1                               |                              2                               |                              3                               |                              4                               |
+| :------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: |
+|    **conv**    | ![0out0anim](https://user-images.githubusercontent.com/41532536/226406989-4726c0f8-2af7-4afe-82b5-3d6679bb6118.gif) | ![0out1anim](https://user-images.githubusercontent.com/41532536/226406897-0a35f296-d6e1-4b24-9e09-4dcf6b5e07f9.gif) | ![0out2anim](https://user-images.githubusercontent.com/41532536/226406816-c4912a9d-551e-43d4-9660-3124a47ca643.gif) | ![0out3anim](https://user-images.githubusercontent.com/41532536/226406738-d3a75d4a-3464-491a-934e-d753be6a71cd.gif) | ![0out4anim](https://user-images.githubusercontent.com/41532536/226406638-fb0a1c33-d49f-4fa2-9367-a2af6c0923fa.gif) |
+|    **relu**    | ![0out0anim](https://user-images.githubusercontent.com/41532536/226403113-64d65811-7855-4fa0-b513-44adcfc22f01.gif) | ![0out1anim](https://user-images.githubusercontent.com/41532536/226403003-88e9f53c-73a4-4276-a0eb-c3ae19231bb8.gif) | ![0out2anim](https://user-images.githubusercontent.com/41532536/226402893-d9475902-e24c-4df2-ab68-af3b7e961988.gif) | ![0out3anim](https://user-images.githubusercontent.com/41532536/226402798-f80a739a-7e23-4ae3-87ee-c1b5fca3353e.gif) | ![0out4anim](https://user-images.githubusercontent.com/41532536/226402685-de4f134a-f95f-40ad-88f3-eb4835eb51c0.gif) |
+
+looking at all the canvases from `conv` and `relu` we can infer that both the layers don't output very different canvases, and its safe to use either of layers for reconstruction.
+
+# Visualization
+
+Until now we have reconstructed canvases using all the style layers and any one content layer, but in this section we will **visualize** the individual and grouped contribution of style and content layers. We have 3 ways to do so, either only visualizing content layer(s), or visualizing style layers(s) or both layers.
+
+shell command to visualize is
+
+```bash
+python3 main.py --visualize "content" --content_layers 1 2 
+```
+
+## Content
+
+when `--visualize "content"` then we can only visualize the content representation of any layer or by grouping some layers.
+
 | Content_Layers |  0   |  1   |  2   |  3   |  4   |
 | :------------: | :--: | :--: | :--: | :--: | :--: |
-|    **conv**    |   ![0out0anim](https://user-images.githubusercontent.com/41532536/226406989-4726c0f8-2af7-4afe-82b5-3d6679bb6118.gif)   |   ![0out1anim](https://user-images.githubusercontent.com/41532536/226406897-0a35f296-d6e1-4b24-9e09-4dcf6b5e07f9.gif)2   |   ![0out2anim](https://user-images.githubusercontent.com/41532536/226406816-c4912a9d-551e-43d4-9660-3124a47ca643.gif)   |   ![0out3anim](https://user-images.githubusercontent.com/41532536/226406738-d3a75d4a-3464-491a-934e-d753be6a71cd.gif)   |   ![0out4anim](https://user-images.githubusercontent.com/41532536/226406638-fb0a1c33-d49f-4fa2-9367-a2af6c0923fa.gif)   |
-|    **relu**    |   ![0out0anim](https://user-images.githubusercontent.com/41532536/226403113-64d65811-7855-4fa0-b513-44adcfc22f01.gif)   |   ![0out1anim](https://user-images.githubusercontent.com/41532536/226403003-88e9f53c-73a4-4276-a0eb-c3ae19231bb8.gif)   |  ![0out2anim](https://user-images.githubusercontent.com/41532536/226402893-d9475902-e24c-4df2-ab68-af3b7e961988.gif)    |  ![0out3anim](https://user-images.githubusercontent.com/41532536/226402798-f80a739a-7e23-4ae3-87ee-c1b5fca3353e.gif)    |   ![0out4anim](https://user-images.githubusercontent.com/41532536/226402685-de4f134a-f95f-40ad-88f3-eb4835eb51c0.gif)   |
+|      conv      |      |      |      |      |      |
+|      relu      |      |      |      |      |      |
 
 
-# Visualization
+
+## Style
+
+## Both